A sociologist explains a little bit more about the Living Earth Simulator that aims to model society:

Time travel: probably not going to happen any time soon. At least, not in the physical, “Back to the Future” sense. But that doesn’t stop us from trying to peek into the future. In the December issue of Scientific American, writer David Weinberger chats with Dirk Helbing, a Swiss physicist and sociologist who is pitching a project called the Living Earth Simulator, a billion-euro computer system that would absorb vast amounts of data, use it to model global-scale systems — economies, governments, etc. — and predict the future.

Well, maybe. Weinberger speaks with researchers who point out the roadblocks. While it’s possible to model small systems, such as highway and pedestrian traffic, getting a read on the economy, the environment and public health all at once is a much more complicated process. For instance, how would you account for feedback loops in the system — that is, what happens when the computer model’s conclusions alter the situation that it’s modeling? And if you can’t understand the process through which the model generates an answer, the whole thing is just a giant Magic 8 Ball, anyway. The computer may call upon world leaders to “set fire to all the world’s oil wells,” writes Weinberger. “That will not be actionable advice if the policymaker cannot explain why it’s right.”

So data mining will not be encouraged or will the model’s supervisors insist that every discovered pattern come with an explanation?

Interestingly, Helbing is also featured in a recent article in The Economist about pedestrian traffic:

In 1995 Mr Helbing and Peter Molnar, both physicists, came up with a “social force” computer model that used insights from the way that particles in fluids and gases behave to describe pedestrian movement. The model assumed that people are attracted by some things, such as the destination they are heading for, and repelled by others, such as another pedestrian in their path. It proved its worth by predicting several self-organising effects among crowds that are visible in real life.

One is the propensity of dense crowds spontaneously to break into lanes that allow people to move more efficiently in opposing directions. Individuals do not have to negotiate their way through a series of encounters with oncoming people; they can just follow the person in front. That works better than trying to overtake. Research by Mr Moussaid suggests that the effect of one person trying to walk faster than the people around them in a dense crowd is to force an opposing lane of pedestrians to split in two, which has the effect of breaking up the lane next door, and so on. Everyone moves slower as a result.

Two quick thoughts:

1. Combining physics and sociology to explain social behavior seems to be growing in popularity. Here is what I assume: the physics side brings experience in dealing with complex models and a more naturalistic way of explaining human behavior while sociologists bring more theories and knowledge about human contingencies. (But I could be wrong.) It does seem like the combination of these two disciplines could uniquely bridge the gap between the natural and social sciences.

2. Overall, I assume there will be many more projects like this. Getting the data is not so much a problem and we have the computing power to calculate complex models. If this does increase, this will mean some changes within the discipline of sociology: a shift toward mathematical sociology (making regression look relatively simple), thinking about “natural laws” in a way that sociology has generally avoided, and viewing the world in a different way (individuals operating within complex systems).